大波动短时公路交通流K近邻预测的稳健组合方法.pdf

文档介绍：第 44 卷第 2 期天津大学学报
2011 年 2 月 Journal of Tianjin University Feb. 2011

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大波动短时公路交通流 K-近邻预测的稳健组合方法
张军 1,2,王寒凝 1,2,杨正瓴 1,2,刘正光 1,2,叶剑华 1,2
(1. 天津大学电气与自动化工程学院,天津 300072;2. 天津市过程检测与控制重点实验室,天津 300072)
摘要:在公路短时交通流预测中,为改善大波动以及离群值情况下的预测效果,提高实时性,对K-近邻非参数回归预
测方法进行了2 种改进:先采用相关系数来选择K-近邻,
替以前的距离,以改善在大波动交通流情况下 K-,以
,可提高预测准确率约 1%.数值仿真证实了2 种改进的效果.
关键词:短时公路交通流预测;非参数回归;相关系数;组合预测;稳健统计
中图分类号:;C812; 文献标志码:A 文章编号:0493-2137(2011)02-0107-06

bination for K-Nearest Neighbors’ Forecasting Under Large
Fluctuant Short-Term Highway Traffic Flows
1,2 1,2 1,2 1,2 1,2
ZHANG Jun ,WANG Han-ning ,YANG Zheng-ling ,LIU Zheng-guang ,YE Jian-hua
(1. School of Electrical Engineering and Automation,Tianjin University,Tianjin 300072,China;
2. Tianjin Key Laboratory of Process Measurement and Control,Tianjin 300072,China)
Abstract:To improve the forecasting effect for large fluctuant traffic flows and shorten putation time in fore-
casting short-term highway traffic flows,two improvements were made to the K-nearest neighbors(K-NNs) non-
parametric regression method. First,instead of distance or norm,correlation coefficient was used to select K-NNs.
Second,the variance reciprocal method bination forecasts was adopted to synthesize the e by K-NNs.
The K-NNs select